Access

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

Biometrics is a scientific journal emphasizing the role of statistics
and mathematics in the biological sciences. Its object is to promote and extend
the use of mathematical and statistical methods in pure and applied biological
sciences by describing developments in these methods and their applications
in a form readily assimilable by experimental scientists.
JSTOR provides a digital archive of the print version of Biometrics.
The electronic version of Biometrics is available at http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code=biom.
Authorized users may be able to access the full text articles at this site.

The "moving wall" represents the time period between the last issue
available in JSTOR and the most recently published issue of a journal.
Moving walls are generally represented in years. In rare instances, a
publisher has elected to have a "zero" moving wall, so their current
issues are available in JSTOR shortly after publication.
Note: In calculating the moving wall, the current year is not counted.
For example, if the current year is 2008 and a journal has a 5 year
moving wall, articles from the year 2002 are available.

Terms Related to the Moving Wall

Fixed walls: Journals with no new volumes being added to the archive.

Absorbed: Journals that are combined with another title.

Complete: Journals that are no longer published or that have been
combined with another title.

Abstract

The ratio of the number of `failures' observed in a sample to the total exposure time is known to be a maximum likelihood, consistent estimator of risk in a homogeneous population with constant risk per unit time. Two models are here presented for both homogeneous and heterogeneous populations that are subject to risks of being lost to observation as well as of failure. The exact distribution of the ratio is derived and approximations are used to study its small sample properties in these populations. For homogeneous populations, the bias in the ratio (which is not large) and its considerable skewness are diminished with increasing sample size but tend to be aggravated with increasing duration of observations. For heterogeneous populations, the expected value of the ratio is a decreasing function of the duration of the observations. Particularly when losses are included, the ratio may be so erratic that it cannot be said to estimate any quantity of interest or to be a meaningful approach to the comparison of several groups.